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make expert model configurable

This commit is contained in:
AI Christianson 2024-12-13 14:19:42 -05:00
parent 571b9474d3
commit 36e00d8227
4 changed files with 107 additions and 4 deletions
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26
README.md
View File

@ -148,6 +148,8 @@ ra-aid -m "Explain the authentication flow" --research-only
- `--cowboy-mode`: Skip interactive approval for shell commands
- `--provider`: Specify the model provider (See Model Configuration section)
- `--model`: Specify the model name (See Model Configuration section)
- `--expert-provider`: Specify the provider for the expert tool (defaults to OpenAI)
- `--expert-model`: Specify the model name for the expert tool (defaults to o1-preview for OpenAI)
### Model Configuration
@ -155,15 +157,23 @@ RA.Aid supports multiple AI providers and models. The default model is Anthropic
The programmer tool (aider) automatically selects its model based on your available API keys. It will use Claude models if ANTHROPIC_API_KEY is set, or fall back to OpenAI models if only OPENAI_API_KEY is available.
Note: The expert tool can be configured to use different providers (OpenAI, Anthropic, OpenRouter) using the --expert-provider flag along with the corresponding EXPERT_*_KEY environment variables. Each provider requires its own API key set through the appropriate environment variable.
#### Environment Variables
RA.Aid supports multiple providers through environment variables:
- `ANTHROPIC_API_KEY`: Required for the default Anthropic provider
- `OPENAI_API_KEY`: Required for OpenAI provider and expert tool
- `OPENAI_API_KEY`: Required for OpenAI provider
- `OPENROUTER_API_KEY`: Required for OpenRouter provider
- `OPENAI_API_BASE`: Required for OpenAI-compatible providers along with `OPENAI_API_KEY`
Expert Tool Environment Variables:
- `EXPERT_OPENAI_KEY`: API key for expert tool using OpenAI provider
- `EXPERT_ANTHROPIC_KEY`: API key for expert tool using Anthropic provider
- `EXPERT_OPENROUTER_KEY`: API key for expert tool using OpenRouter provider
- `EXPERT_OPENAI_BASE`: Base URL for expert tool using OpenAI-compatible provider
You can set these permanently in your shell's configuration file (e.g., `~/.bashrc` or `~/.zshrc`):
```bash
@ -180,7 +190,7 @@ export OPENROUTER_API_KEY=your_api_key_here
export OPENAI_API_BASE=your_api_base_url
```
Note: The expert tool always uses OpenAI's `o1-preview` model and requires `OPENAI_API_KEY` to be set, even if you're using a different provider for the main application.
Note: The expert tool defaults to OpenAI's o1-preview model with the OpenAI provider, but this can be configured using the --expert-provider flag along with the corresponding EXPERT_*_KEY environment variables.
#### Examples
@ -203,6 +213,18 @@ Note: The expert tool always uses OpenAI's `o1-preview` model and requires `OPEN
ra-aid -m "Your task" --provider openrouter --model mistralai/mistral-large-2411
```
4. **Configuring Expert Provider**
```bash
# Use Anthropic for expert tool
ra-aid -m "Your task" --expert-provider anthropic
# Use OpenRouter for expert tool
ra-aid -m "Your task" --expert-provider openrouter
# Use default OpenAI for expert tool
ra-aid -m "Your task" --expert-provider openai
```
**Important Notes:**
- Performance varies between models. The default Claude 3 Sonnet model currently provides the best and most reliable results.
- Model configuration is done via command line arguments: `--provider` and `--model`

37
ra_aid/__main__.py
View File

@ -67,6 +67,18 @@ Examples:
action='store_true',
help='Skip interactive approval for shell commands'
)
parser.add_argument(
'--expert-provider',
type=str,
default='openai',
choices=['anthropic', 'openai', 'openrouter', 'openai-compatible'],
help='The LLM provider to use for expert knowledge queries (default: openai)'
)
parser.add_argument(
'--expert-model',
type=str,
help='The model name to use for expert knowledge queries (required for non-OpenAI providers)'
)
args = parser.parse_args()
@ -77,6 +89,10 @@ Examples:
elif not args.model:
parser.error(f"--model is required when using provider '{args.provider}'")
# Validate expert model requirement
if args.expert_provider != 'openai' and not args.expert_model:
parser.error(f"--expert-model is required when using expert provider '{args.expert_provider}'")
return args
# Create console instance
@ -256,6 +272,7 @@ def validate_environment(args):
"""
missing = []
provider = args.provider
expert_provider = args.expert_provider
# Check API keys based on provider
if provider == "anthropic":
@ -273,6 +290,22 @@ def validate_environment(args):
if not os.environ.get('OPENAI_API_BASE'):
missing.append('OPENAI_API_BASE environment variable is not set')
# Check expert provider keys
if expert_provider == "anthropic":
if not os.environ.get('EXPERT_ANTHROPIC_KEY'):
missing.append('EXPERT_ANTHROPIC_KEY environment variable is not set')
elif expert_provider == "openai":
if not os.environ.get('EXPERT_OPENAI_KEY'):
missing.append('EXPERT_OPENAI_KEY environment variable is not set')
elif expert_provider == "openrouter":
if not os.environ.get('EXPERT_OPENROUTER_KEY'):
missing.append('EXPERT_OPENROUTER_KEY environment variable is not set')
elif expert_provider == "openai-compatible":
if not os.environ.get('EXPERT_OPENAI_KEY'):
missing.append('EXPERT_OPENAI_KEY environment variable is not set')
if not os.environ.get('EXPERT_OPENAI_BASE'):
missing.append('EXPERT_OPENAI_BASE environment variable is not set')
if missing:
print_error("Missing required dependencies:")
for item in missing:
@ -307,6 +340,10 @@ def main():
# Store config in global memory for access by is_informational_query
_global_memory['config'] = config
# Store expert provider and model in config
_global_memory['config']['expert_provider'] = args.expert_provider
_global_memory['config']['expert_model'] = args.expert_model
# Run research stage
print_stage_header("Research Stage")

42
ra_aid/llm.py
View File

@ -43,3 +43,45 @@ def initialize_llm(provider: str, model_name: str) -> BaseChatModel:
)
else:
raise ValueError(f"Unsupported provider: {provider}")
def initialize_expert_llm(provider: str = "openai", model_name: str = "o1-preview") -> BaseChatModel:
"""Initialize an expert language model client based on the specified provider and model.
Note: Environment variables must be validated before calling this function.
Use validate_environment() to ensure all required variables are set.
Args:
provider: The LLM provider to use ('openai', 'anthropic', 'openrouter', 'openai-compatible').
Defaults to 'openai'.
model_name: Name of the model to use. Defaults to 'o1-preview'.
Returns:
BaseChatModel: Configured expert language model client
Raises:
ValueError: If the provider is not supported
"""
if provider == "openai":
return ChatOpenAI(
openai_api_key=os.getenv("EXPERT_OPENAI_KEY"),
model=model_name
)
elif provider == "anthropic":
return ChatAnthropic(
anthropic_api_key=os.getenv("EXPERT_ANTHROPIC_KEY"),
model=model_name
)
elif provider == "openrouter":
return ChatOpenAI(
openai_api_key=os.getenv("EXPERT_OPENROUTER_KEY"),
openai_api_base="https://openrouter.ai/api/v1",
model=model_name
)
elif provider == "openai-compatible":
return ChatOpenAI(
openai_api_key=os.getenv("EXPERT_OPENAI_KEY"),
openai_api_base=os.getenv("EXPERT_OPENAI_BASE"),
model=model_name
)
else:
raise ValueError(f"Unsupported provider: {provider}")

6
ra_aid/tools/expert.py
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@ -4,7 +4,7 @@ from langchain_core.tools import tool
from rich.console import Console
from rich.panel import Panel
from rich.markdown import Markdown
from langchain_openai import ChatOpenAI
from ..llm import initialize_expert_llm
from .memory import get_memory_value, get_related_files
console = Console()
@ -13,7 +13,9 @@ _model = None
def get_model():
global _model
if _model is None:
_model = ChatOpenAI(model_name="o1-preview")
provider = get_memory_value('expert_provider') or 'openai'
model = get_memory_value('expert_model') or 'o1-preview'
_model = initialize_expert_llm(provider, model)
return _model
# Keep track of context globally